Conversation analysis characterizes the order and structure of human spoken communication. Conversation can be formal, such as used in a courtroom, or more casual, as in a chat between old friends. One fundamental component of all interpersonal conversation, though, is turn-taking, whereby participants talk one at-a-time. Brief and short gaps in conversation often occur. Longer gaps, however, may indicate a pause in the conversation, a hesitation among the speakers, or a change in topic. As a result, conversation analysis involves consideration of both audible and temporal aspects.
Conversation is also dynamic. When groups of people gather, a main conversation might branch into subconversations between a subset of the participants. For example, coworkers discussing the weather may branch into a talk about one co-worker's weekend, while another part of the group debates the latest blockbuster movie. An individual involved in one discussion would find simultaneously following the other conversation difficult. Cognitive limits on human attention force him to focus his attention on only one conversation.
Passive listening is complicated by the dynamics of active conversation, such as where an individual is responsible for simultaneously monitoring multiple conversations. For example, a teacher may be listening to multiple groups of students discuss their class projects. Although the teacher must track each group's progress, simultaneously listening to and comprehending more than one conversation in detail is difficult, again due to cognitive limits on attention.
Notwithstanding, the human selective attention process enables a person to overhear or focus on certain words, even when many other conversations are occurring simultaneously. For example, an individual tends to overhear her name mentioned in another conversation, even if she is attentive to some other activity. Thus, the teacher would recognize her name being spoken by one student group even if she was listening to another group. These “high meaning” words have a lower attention activation threshold since they have more “meaning” to the listener. Each person's high meaning words are finite and context-dependent, and a large amount of subconversation may still be ignored or overlooked due to the limits, and inherent unreliability, of the selective attention process.
As well, cognition problems that occur when attempting to follow multiple simultaneous conversations are compounded when the participants are physically removed from one another. For instance, teleconferencing and shared-channel communications systems allow groups of participants to communicate remotely. Conversations between participants are mixed together on the same media channel and generally received by each group over a single set of speakers, which hampers following more than one conversation at a time. Moreover, visual cues may not be available and speaker identification becomes difficult.
Current techniques for managing simultaneous conversations place audio streams into separate media channels, mute or lower the volume of conversations in which a participant is not actively engaged, and use spatialization techniques to change the apparent positions of conversants. These techniques, however, primarily emphasize a main conversation to the exclusion of other conversations and noises.
Therefore, an approach is needed to facilitate monitoring multiple simultaneous remote conversations. Preferably, such an approach would mimic and enhance the human selective attention process and allow participants to notice those remote communications of likely importance to them, which occur in subconversations ongoing at the same time as a main conversation.